Tootfinder

Enhancing Traffic Accident Classifications: Application of NLP Methods for City Safety
Enes \"Ozeren, Alexander Ulbrich, Sascha Filimon, David R\"ugamer, Andreas Bender
https://arxiv.org/abs/2506.12092

Enhancing Traffic Accident Classifications: Application of NLP Methods for City Safety
A comprehensive understanding of traffic accidents is essential for improving city safety and informing policy decisions. In this study, we analyze traffic incidents in Munich to identify patterns and characteristics that distinguish different types of accidents. The dataset consists of both structured tabular features, such as location, time, and weather conditions, as well as unstructured free-text descriptions detailing the circumstances of each accident. Each incident is categorized into on…

A Unified Framework for Probabilistic Dynamic-, Trajectory- and Vision-based Virtual Fixtures
Maximilian M\"uhlbauer, Freek Stulp, Sylvain Calinon, Alin Albu-Sch\"affer, Jo\~ao Silv\'erio
https://arxiv.org/abs/2506.10239

A Unified Framework for Probabilistic Dynamic-, Trajectory- and Vision-based Virtual Fixtures
Probabilistic Virtual Fixtures (VFs) enable the adaptive selection of the most suitable haptic feedback for each phase of a task, based on learned or perceived uncertainty. While keeping the human in the loop remains essential, for instance, to ensure high precision, partial automation of certain task phases is critical for productivity. We present a unified framework for probabilistic VFs that seamlessly switches between manual fixtures, semi-automated fixtures (with the human handling precise…